Medical Care最新文献

{"title":"Children and Youth Are a Critical Part of the American Story of Homelessness.","authors":"Gregory D Stevens","doi":"10.1097/MLR.0000000000002052","DOIUrl":"10.1097/MLR.0000000000002052","url":null,"abstract":"","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141906981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations of Homelessness With Primary Care and Acute Care Utilization Among Medicaid-Enrolled Youth.","authors":"Dahai Yue, Emmeline Chuang, Weihao Zhou, Elsie A Essien, Youngeun Lee, Brenna O'Masta, Nadereh Pourat","doi":"10.1097/MLR.0000000000002009","DOIUrl":"10.1097/MLR.0000000000002009","url":null,"abstract":"<p><strong>Background: </strong>Youth comprise one-third of the US homeless population. However, little is known about how homelessness affects health care utilization.</p><p><strong>Objective: </strong>Examine associations of homelessness with hospitalization, primary care, and ED visits, varying by race/ethnicity, among Medicaid-enrolled youth.</p><p><strong>Research design: </strong>A cross-sectional analysis was conducted using California Medicaid claims data on youth beneficiaries with complex needs. We examined the number of hospitalizations, preventable and nonpreventable ED, and primary care visits using a multivariate regression. We further explored the differential associations by race/ethnicity.</p><p><strong>Results: </strong>Approximately 17% of our sampled youth experienced homelessness in 2018 (N=90,202). Compared with their housed counterparts, youth experiencing homelessness had a 1.9 percentage point (pp) higher likelihood of frequent ED visits (95% CI: 1.7-2.2) but a 2.9 pp lower probability of any primary care visits (95% CI: -3.9 to -1.9). Homelessness was associated with 221 more ED visits (95% CI: 182-260), 100 more preventable ED visits (95% CI: 84-116), 19.9 more hospitalizations (95% CI: 12-27), but 56 fewer primary care visits (95% CI: -104 to -7), per 1000 youth. The associations of homelessness with total ED visits, preventable ED visits, and needed and nonpreventable ED visits were all higher among Whites and, particularly, Blacks than for Hispanics and Asians.</p><p><strong>Conclusions: </strong>Medicaid-enrolled youth who experienced homelessness had more overall ED, preventable ED, and hospital visits, but fewer primary care visits than their housed peers. Our results suggest promoting primary care use should be considered among strategies to improve health and reduce costs.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141075709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conducting Comparative Effectiveness, Multisite Palliative Care and Advance Care Planning Trials: Lessons Learned and Future Directions From PCORI-Funded Studies.","authors":"Areej El-Jawahri, Brittany Waterman, Susan Enguidanos, Lisa Gibbs, Victor Navarro, Maren Olsen, Jennifer Temel, Annette Totten, Corita R Grudzen","doi":"10.1097/MLR.0000000000002042","DOIUrl":"10.1097/MLR.0000000000002042","url":null,"abstract":"<p><p>The Patient-Centered Outcomes Research Institute (PCORI) funded multiple large-scale comparative effectiveness clinical trials evaluating palliative care (PC) and advance care planning (ACP) healthcare delivery models. This article provides an overview of the most common barriers our investigative teams encountered while implementing these trials and the strategies we utilized to overcome these challenges, with particular attention to identifying research partners for multisite trials; addressing contracting and regulatory issues; creating a team governance structure; training and engaging study staff across sites; recruiting, consenting, and enrolling study participants; collecting PC and ACP data and study outcomes; and managing multisite collaborations. The goal of this article is to provide guidance on how to best plan for and conduct rigorous trials evaluating PC and ACP healthcare delivery interventions moving forward.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11373889/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142154537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Palliative Care and Advance Care Planning Intervention Fidelity Monitoring: Methods and Lessons Learned From PCORI-Funded Large-Scale, Pragmatic Clinical Trials.","authors":"Manisha Verma, Corita R Grudzen, Seiko Izumi, Neil Wenger, Areej El-Jawahri, Deborah Ejem, Rebecca A Aslakson","doi":"10.1097/MLR.0000000000002037","DOIUrl":"10.1097/MLR.0000000000002037","url":null,"abstract":"<p><p>Over the past decade, the Patient-Centered Outcomes Research Institute (PCORI) funded multiple large-scale, comparative effectiveness clinical trials evaluating palliative care and advance care planning interventions. These are complex multicomponent interventions that need robust but flexible fidelity monitoring. Fidelity is necessary to maintain both internal and external validity within palliative care intervention research and to ultimately evaluate the real-world impact of high-quality interventions. Different trials not only took varying approaches to fidelity monitoring but also uncovered both unique and common challenges and facilitators. This article summarizes 8 of these trials and highlights approaches, adaptations, barriers, and facilitators for intervention fidelity monitoring. Identifying and delivering core elements while simultaneously allowing adaptations of noncore elements is a vital part of fidelity monitoring. Dissemination of such experiences can inform both future palliative care research as well as ongoing implementation of palliative care and advance care planning interventions across diverse clinical practices. Adoption of rigorous intervention fidelity methods is critical to advancing the science and reproducibility of palliative care interventions.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11373891/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142154540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends in Common Ownership among Insurers in Medicare Part D.","authors":"Pinka Chatterji, Chun-Yu Ho, Alyssa Kamara, Jaehak Lee","doi":"10.1097/MLR.0000000000002030","DOIUrl":"10.1097/MLR.0000000000002030","url":null,"abstract":"<p><strong>Background: </strong>Recent studies document the rising prevalence of common ownership by institutional investors in specific industries. Those investors offer products, such as mutual and index funds, to trade securities on behalf of others and often own shares of multiple firms in the same industry to diversify portfolios. However, at present, few studies focus on common ownership trends in health care.</p><p><strong>Objectives: </strong>This paper examines institutional investors' common ownership in the major insurers offering plans in the Medicare Part D stand-alone prescription drug plan (PDP) market between 2013 and 2020.</p><p><strong>Research design: </strong>Using data from the Securities and Exchange Commission (SEC) database and the Center for Research in Securities Prices, we compute the percentages of outstanding shares of each insurer owned by institutional investors. Data visualization and network analysis are employed to assess the trends in common ownership among major insurers.</p><p><strong>Results: </strong>We document a high prevalence of and substantial increase in shared institutional investors in the PDP market. From 2013 to 2020, the degree of common ownership increased by 7% on average, and the common ownership network became more connected. Common ownership also varies across the 34 PDP regions depending on their reliance on listed insurers, that are traded in the stock exchange, offering stand-alone PDPs.</p><p><strong>Conclusions: </strong>High and rising common ownership in the Medicare Part D PDP market raises policy questions about potential effects on plan offerings, premiums, and quality for consumers.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11315633/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141580203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Nurse Residency Program on Time-to-Fill Nurse Vacancies at the Veterans Health Administration.","authors":"Yufei Li, Aaron Legler, Aigerim Kabdiyeva, PhiYen Nguyen, Melissa Garrido, Steven Pizer","doi":"10.1097/MLR.0000000000002032","DOIUrl":"10.1097/MLR.0000000000002032","url":null,"abstract":"<p><strong>Background: </strong>The Department of Veterans Affairs (VA) offers a 1-year Post-Baccalaureate-Registered Nurse Residency (PB-RNR) Program. The impact of the PB-RNR program on local RN recruitment was unknown.</p><p><strong>Objectives: </strong>We aimed to evaluate the effect of the size of the PB-RNR program at a VA facility on its time-to-fill RN vacancies.</p><p><strong>Project design: </strong>We used an instrumental variable approach with a 2-stage residual inclusion specification.</p><p><strong>Subjects: </strong>We included RN filled vacancies in the VA that were posted nationwide between 2020 and 2021.</p><p><strong>Measures: </strong>Our independent variable was the facility-year level number of PB-RNR program allocations. The 3 binary outcomes were whether the RN vacancy was filled within 90, 60, or 30 days.</p><p><strong>Results: </strong>An increase of one training allocation was significantly associated with a 5.60 percentage point (PP) (95% CI: 2.74-8.46) higher likelihood of filling a vacancy within 90 days, 7.34 PP (95% CI: 4.66-10.03) higher likelihood of filling a vacancy within 60 days, and 5.32 PP (95% CI: 3.18-7.46) higher likelihood of filling a vacancy within 30 days. The impact was significant in both 2020 and 2021 positions, and in facilities located in areas with lower social deprivation scores, higher-quality public schools, or with either no or partial primary care physician shortages.</p><p><strong>Conclusions: </strong>We found favorable impacts of the size of the PB-RNR program at a VA facility on filling RN vacancies.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141580202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hospital Presumptive Eligibility Emergency Medicaid Programs: An Opportunity for Continuous Insurance Coverage?","authors":"Lisa Marie Knowlton, Katherine Arnow, Amber W Trickey, Linda D Tran, Alex H S Harris, Arden M Morris, Todd H Wagner","doi":"10.1097/MLR.0000000000002026","DOIUrl":"10.1097/MLR.0000000000002026","url":null,"abstract":"<p><strong>Background: </strong>Lack of health insurance is a public health crisis, leading to foregone care and financial strain. Hospital Presumptive Eligibility (HPE) is a hospital-based emergency Medicaid program that provides temporary (up to 60 d) coverage, with the goal that hospitals will assist patients in applying for ongoing Medicaid coverage. It is unclear whether HPE is associated with successful longer-term Medicaid enrollment.</p><p><strong>Objective: </strong>To characterize Medicaid enrollment 6 months after initiation of HPE and determine sociodemographic, clinical, and geographic factors associated with Medicaid enrollment.</p><p><strong>Design: </strong>This was a cohort study of all HPE approved inpatients in California, using claims data from the California Department of Healthcare Services.</p><p><strong>Setting: </strong>The study was conducted across all HPE-participating hospitals within California between January 1, 2016 and December 31, 2017.</p><p><strong>Participants: </strong>We studied California adult hospitalized inpatients, who were uninsured at the time of hospitalization and approved for HPE emergency Medicaid. Using multivariable logistic regression models, we compared HPE-approved patients who enrolled in Medicaid by 6 months versus those who did not.</p><p><strong>Exposures: </strong>HPE emergency Medicaid approval at the time of hospitalization.</p><p><strong>Main outcomes and measures: </strong>The primary outcome was full-scope Medicaid enrollment by 6 months after the hospital's presumptive eligibility approval.</p><p><strong>Results: </strong>Among 71,335 inpatient HPE recipients, a total of 45,817 (64.2%) enrolled in Medicaid by 6 months. There was variability in Medicaid enrollment across counties in California (33%-100%). In adjusted analyses, Spanish-preferred-language patients were less likely to enroll in Medicaid (aOR 0.77, P <0.001). Surgical intervention (aOR 1.10, P <0.001) and discharge to another inpatient facility or a long-term care facility increased the odds of Medicaid enrollment (vs. routine discharge home: aOR 2.24 and aOR 1.96, P <0.001).</p><p><strong>Conclusion: </strong>California patients who enroll in HPE often enroll in Medicaid coverage by 6 months, particularly among patients requiring surgical intervention, repeated health care visits, and ongoing access to care. Future opportunities include prospective evaluation of HPE recipients to understand the impact that Medicaid enrollment has on health care utilization and financial solvency.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11315624/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141580201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends in Sexual Orientation and Gender Identity Data Collection.","authors":"Ulrike Boehmer, Amy M LeClair, Bill M Jesdale","doi":"10.1097/MLR.0000000000002036","DOIUrl":"10.1097/MLR.0000000000002036","url":null,"abstract":"<p><strong>Objective: </strong>The aim of this study was to determine response patterns to sexual orientation and gender identity (SOGI) questions in the Behavioral Risk Factor Surveillance System (BRFSS) over time and to assess nonresponse and indeterminate responses by demographic characteristics.</p><p><strong>Methods: </strong>This is a secondary data analysis of the SOGI module of the BRFSS. We used data from 46 states and Guam that implemented SOGI questions between 2014 and 2022. We used weighted analyses that accounted for the sampling design, determined SOGI response patterns by year, and assessed nonresponse and indeterminate responses by demographic characteristics.</p><p><strong>Results: </strong>Over time, increasing numbers self-reported as sexual and gender minority respondents, while heterosexual identity declined. Sexual orientation nonresponse and indeterminate responses increased with time, while respondents' reports of not knowing gender identity declined. Hispanic, older, respondents, those with lower education, and those who completed the questionnaire in Spanish had higher SOGI nonresponse and indeterminate responses.</p><p><strong>Conclusions: </strong>The low amount of SOGI nonresponse and indeterminate responses in the BRFSS can be instructive for the implementation of SOGI questions in medical settings. SOGI data collection in all settings requires improving procedures for the groups that have been shown to have elevated nonresponse and indeterminate response.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141580204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting Self-Reported Social Risk in Medically Complex Adults Using Electronic Health Data.","authors":"Richard W Grant, Jodi K McCloskey, Connie S Uratsu, Dilrini Ranatunga, James D Ralston, Elizabeth A Bayliss, Oleg Sofrygin","doi":"10.1097/MLR.0000000000002021","DOIUrl":"10.1097/MLR.0000000000002021","url":null,"abstract":"<p><strong>Background: </strong>Social barriers to health care, such as food insecurity, financial distress, and housing instability, may impede effective clinical management for individuals with chronic illness. Systematic strategies are needed to more efficiently identify at-risk individuals who may benefit from proactive outreach by health care systems for screening and referral to available social resources.</p><p><strong>Objective: </strong>To create a predictive model to identify a higher likelihood of food insecurity, financial distress, and/or housing instability among adults with multiple chronic medical conditions.</p><p><strong>Research design and subjects: </strong>We developed and validated a predictive model in adults with 2 or more chronic conditions who were receiving care within Kaiser Permanente Northern California (KPNC) between January 2017 and February 2020. The model was developed to predict the likelihood of a \"yes\" response to any of 3 validated self-reported survey questions related to current concerns about food insecurity, financial distress, and/or housing instability. External model validation was conducted in a separate cohort of adult non-Medicaid KPNC members aged 35-85 who completed a survey administered to a random sample of health plan members between April and June 2021 (n = 2820).</p><p><strong>Measures: </strong>We examined the performance of multiple model iterations by comparing areas under the receiver operating characteristic curves (AUCs). We also assessed algorithmic bias related to race/ethnicity and calculated model performance at defined risk thresholds for screening implementation.</p><p><strong>Results: </strong>Patients in the primary modeling cohort (n = 11,999) had a mean age of 53.8 (±19.3) years, 64.7% were women, and 63.9% were of non-White race/ethnicity. The final, simplified model with 30 predictors (including utilization, diagnosis, behavior, insurance, neighborhood, and pharmacy-based variables) had an AUC of 0.68. The model remained robust within different race/ethnic strata.</p><p><strong>Conclusions: </strong>Our results demonstrated that a predictive model developed using information gleaned from the medical record and from public census tract data can be used to identify patients who may benefit from proactive social needs assessment. Depending on the prevalence of social needs in the target population, different risk output thresholds could be set to optimize positive predictive value for successful outreach. This predictive model-based strategy provides a pathway for prioritizing more intensive social risk outreach and screening efforts to the patients who may be in greatest need.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141248148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Collaborative Care Cost-Sharing and Referral Rates in Colorado.","authors":"Betsy Q Cliff, Tiffany H Xie, Neda Laiteerapong","doi":"10.1097/MLR.0000000000002033","DOIUrl":"10.1097/MLR.0000000000002033","url":null,"abstract":"<p><strong>Background: </strong>Collaborative care integrates mental health treatment into primary care and has been shown effective. Yet even in states where its use has been encouraged, take-up remains low and there are potential financial barriers to care.</p><p><strong>Objective: </strong>Describe patient out-of-pocket costs and variations in referral patterns for collaborative care in Colorado.</p><p><strong>Research design: </strong>Retrospective observational study using administrative medical claims data to identify outpatient visits with collaborative care. For individuals with ≥1 visit, we measure spending and visits at the month level. Among physicians with billings for collaborative care, we measure prevalence of eligible patients with collaborative care utilization.</p><p><strong>Subjects: </strong>Patients with Medicare, Medicare Advantage, or commercial health insurance in Colorado, 2018-2019.</p><p><strong>Outcomes: </strong>Out-of-pocket costs (enrollee payments to clinicians), total spending (insurer+enrollee payments to clinicians), percent of patients billed collaborative care.</p><p><strong>Results: </strong>Median total spending (insurer+patient cost) was $48.32 (IQR: $41-$53). Median out-of-pocket cost per month in collaborative care was $8.35 per visit (IQR: $0-$10). Patients with commercial insurance paid the most per month (median: $15); patients with Medicare Advantage paid the least (median: $0). Among clinicians billing for collaborative care (n=193), a mean of 12 percent of eligible patients utilized collaborative care; family practice and advanced practice clinicians' patients utilized it most often.</p><p><strong>Conclusions: </strong>Collaborative care remains underused with fewer than 1 in 6 potentially eligible patients receiving care in this setting. Out-of-pocket costs varied, though were generally low; uncertainty about costs may contribute to low uptake.</p>","PeriodicalId":18364,"journal":{"name":"Medical Care","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141580199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}